The Future of MPI William Gropp Argonne National Laboratory gropp

The Future of MPI

William GroppArgonne National Laboratory

www.mcs.anl.gov/~gropp

University of Chicago Department of Energy

The Success of MPI

• Applications Most recent Gordon Bell prize winners use MPI

• Libraries Growing collection of powerful software components

• Tools Performance tracing (Vampir, Jumpshot, etc.) Debugging (Totalview, etc.)

• Results Papers: http://www.mcs.anl.gov/mpi/papers

• Clusters Ubiquitous parallel computing


Why Was MPI Successful?

• It address all of the following issues: Portability Performance Simplicity and Symmetry Modularity Composability Completeness


Portability and Performance

• Portability does not require a “lowest common denominator” approach Good design allows the use of special,

performance enhancing features without requiring hardware support

MPI’s nonblocking message-passing semantics allows but does not require “zero-copy” data transfers

• BTW, it is “Greatest Common Denominator”


Simplicity and Symmetry

• MPI is organized around a small number of concepts The number of routines is not a good

measure of complexity Fortran

• Large number of intrinsic functions C and Java runtimes are large Development Frameworks

• Hundreds to thousands of methods This doesn’t bother millions of programmers


Measuring Complexity

• Complexity should be measured in the number of concepts, not functions or size of the manual

• MPI is organized around a few powerful concepts Point-to-point message passing Datatypes Blocking and nonblocking buffer handling Communication contexts and process

groups


Elegance of Design

• MPI often uses one concept to solve multiple problems

• Example: Datatypes Describe noncontiguous data transfers,

necessary for performance Describe data formats, necessary for

heterogeneous systems

• “Proof” of elegance: Datatypes exactly what is needed for high-

performance I/O, added in MPI-2.


Parallel I/O

• Collective model provides high I/O performance Matches applications most general view:

objects, distributed among processes

• MPI Datatypes extend I/O model to noncontiguous data in both memory and file Unix readv/writev only applies to memory


Parallel I/O Performance with MPI-IO

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Structured Mesh I/O

Unstructured Grid I/O

Posix style I/O

(Posix too slow to show)


Modularity

• Modern algorithms are hierarchical Do not assume that all operations involve all

or only one process Provide tools that don’t limit the user

• Modern software is built from components MPI designed to support libraries Many applications have no explicit MPI calls;

all MPI contained within well-designed libraries


Composability

• Environments are built from components Compilers, libraries, runtime systems MPI designed to “play well with others”

• MPI exploits newest advancements in compilers … without ever talking to compiler writers OpenMP is an example


Completeness

• MPI provides a complete parallel programming model and avoids simplifications that limit the model Contrast: Models that require that

synchronization only occurs collectively for all processes or tasks

• Make sure that the functionality is there when the user needs it Don’t force the user to start over with a new

programming model when a new feature is needed


Is Ease of Use the Overriding Goal?

• MPI often described as “the assembly language of parallel programming”

• C and Fortran have been described as “portable assembly languages”

• Ease of use is important. But completeness is more important. Don’t force users to switch to a different

approach as their application evolves


Lessons From MPI

• A general programming model for high-performance technical computing must address many issues to succeed

• Even that is not enough. Also needs: Good design Buy-in by the community Effective implementations

• MPI achieved these through an Open Standards Process


An Open and Balanced Process

• Balanced representation from Users

• What users want and need Including correctness

Implementers (Vendors)• What can be provided

Many MPI features determined by implementation needs

Researchers• Directions and Futures

MPI planned for interoperation with OpenMP before OpenMP conceived

Support for libraries strongly influenced by research


Where Next?

• Improving MPI Simplifying and enhancing the expression of MPI

programs

• Improving MPI Implementations Performance Performance Performance

• New Directions What can displace (or complement) MPI?

(Yesterday’s panel presentation on programming models project and tomorrow’s panel on the future of supercomputing)


Improving MPI

• Simpler interfaces Use compiler or precompiler techniques to support simpler, integrated

syntax Fortran 95 arrays, datatypes in C/C++

• Eliminate function calls Use program analysis and transformation to inline operations

• More tools for correctness and performance debugging MPI profiling interface is a good start Debugger interface used by Totalview is an example of tool

development Effort to provide a common interface to internal performance data,

such as idle time waiting for a message• Changes to MPI

E.g., MPI-2 RMA lacks a read-modify-write But don’t hold your breath

• These require research and experimentation before they are ready for a standardization process


Improving MPI Implementations

• Faster Point-to-point Some current implementations make unnecessary copies

• Collective operations Better algorithms exist

• SMP optimizations• Scatter-gather broadcast, reduce, etc.

• Optimizing for new hardware RDMA networks NIC-enabled remote atomic operations

• Wide area networks Optimizations for high latency Speculative sends Quality of service extensions (through MPI attributes)

• Massive scaling Many implementations optimize internal buffers for modest numbers of

processes Some MPI routines (e.g., MPI_Graph_create) do not have scalable definitions


More Improvements for MPI Implementations

• Reduce latency Automatic techniques to compress code paths Closer match to hardware capabilities

• Improve RMA Many current implementations at best functional

• Parallel I/O, particularly for clusters Communication aggregation Reliability in the presence of faults

• Fault tolerance Exploit MPI Intercommunicators to generalize the two-party model

• Thread safe and efficient implementations Lock-free design Software engineering for common MPI implementation source tree

• Many groups working on improved MPI implementations MPICH-2 is an all-new and efficient implementation

• Includes many of these ideas• Designed, as MPICH was, to encourage others to experiment and extend MPI


What’s New in MPICH2

• Beta-test version available for groups that expect to perform research on MPI implementations with MPICH2 Version 0.92 released last Friday

• Contains All of MPI-1, MPI-I/O, service functions from MPI-2, active-

target RMA C, C++, Fortran 77 bindings Example devices for TCP, Infiniband, shared memory Documentation

• Passes extensive correctness tests Intel test suite (as corrected); good unit test suite MPICH test suite; adequate system test suite Notre Dame C++ tests, based on IBM C test suite Passes more tests than MPICH1


MPICH2 Research

• All new implementation is our vehicle for research in Thread safety and efficiency (e.g., avoid thread locks) Optimized MPI datatypes Optimized Remote Memory Access (RMA) High Scalability (64K MPI processes and more) Exploiting Remote Direct Memory Access (RDMA) capable

networks All of MPI-2, including dynamic process management, parallel

I/O, RMA Usability and Robustness

• Software engineering techniques that automate and simplify creating and maintaining a solid, user-friendly implementation

• Allow extensive runtime error checking but do not require it• Integrated performance debugging

Clean interfaces to other system components such as scalable process managers


Some Target Platforms

• Clusters (TCP, UDP, Infiniband, Myrinet, Proprietary Interconnects, …)

• Clusters of SMPs• Grids (UDP, TCP, Globus I/O, …)• Cray Red Storm• BlueGene/x

64K processors; 64K address spaces ANL/IBM developing MPI for BG/L

• QCDoC• Cray X1 (at least I/O)• Other systems


(Logical) Structure of MPICH-2

ADI-3ADIO

MPICH-2

Other parallel file systems

PMI

MPD

Vendors

ChannelInterface

Myrinet,Other NIC

Multi-Method

BG/L

Portals

MM

Existing

In Progress

For others

Fork

PVFS

TCP

Unix(python)

Windows

shmem

TCP shmem Infiniband

remshell

XFS

NFS

HFS SFS

bproc


Conclusions

• The Future of MPI is Bright! Higher-performance implementations More libraries and applications Better tools for developing and tuning MPI

programs Leverage of complementary technologies

• Full MPI-2 implementations will become common Several already exist; many ES apps use

MPI RMA

Documents

The Future of MPI William Gropp Argonne National Laboratory gropp